Predictive Energy Management Strategies for Hybrid Electric Vehicles: Fuel Economy Improvement and Battery Capacity Sensitivity Analysis

2018 ◽  
Author(s):  
Nicolo Cavina ◽  
Gabriele Caramia ◽  
Stefano Patassa ◽  
Michele Caggiano
Keyword(s):  
Sensitivity Analysis ◽  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Battery Capacity ◽  
Fuel Economy Improvement ◽  
Hybrid Electric

scholarly journals A Review of Optimal Energy Management Strategies for Hybrid Electric Vehicle

2014 ◽  
Vol 2014 ◽  
pp. 1-19 ◽  
Author(s):  
Aishwarya Panday ◽  
Hari Om Bansal
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Control Strategies ◽  
Management Strategies ◽  
Energy Optimization ◽  
Hybrid Vehicles ◽  
Power Split ◽  
Hybrid Electric

Presence of an alternative energy source along with the Internal Combustion Engine (ICE) in Hybrid Electric Vehicles (HEVs) appeals for optimal power split between them for minimum fuel consumption and maximum power utilization. Hence HEVs provide better fuel economy compared to ICE based vehicles/conventional vehicle. Energy management strategies are the algorithms that decide the power split between engine and motor in order to improve the fuel economy and optimize the performance of HEVs. This paper describes various energy management strategies available in the literature. A lot of research work has been conducted for energy optimization and the same is extended for Plug-in Hybrid Electric Vehicles (PHEVs). This paper concentrates on the battery powered hybrid vehicles. Numerous methods are introduced in the literature and based on these, several control strategies are proposed. These control strategies are summarized here in a coherent framework. This paper will serve as a ready reference for the researchers working in the area of energy optimization of hybrid vehicles.

Real-time predictive energy management of plug-in hybrid electric vehicles for coordination of fuel economy and battery degradation

Energy ◽  
2021 ◽  
Vol 214 ◽  
pp. 119070
Author(s):  
Ningyuan Guo ◽  
Xudong Zhang ◽  
Yuan Zou ◽  
Lingxiong Guo ◽  
Guodong Du
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Fuel Economy ◽  
Hybrid Electric Vehicles ◽  
Battery Degradation ◽  
Hybrid Electric

Innovative Antriebe 2018

2018 ◽  
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management System ◽  
Hybrid Electric Vehicles ◽  
Management Strategies ◽  
Battery Management System ◽  
Use Case ◽  
Battery Management ◽  
Hybrid Electric

Zukünftiges Mobilitätsverhalten Mobilität 2050 – Selfdriving-eCo-Hyperflyyer, Drahtesel, oder was? . . . . . . . . . . . . . . . . . . .1 K. C. Keller, Aveniture GmbH, Freinsheim Ökobilanzierung Einfluss von Zellbauform und Zellchemie auf die Ökobilanz von batterieelektrischen Fahrzeugen . . . . . . . . . .5 T. Semper, M. Clauß, IAV GmbH, Stollberg; A. Forell, IAV GmbH, Bad Cannstatt Anwendungsfallabhängige CO2 -Bilanzen elektrifizierter Fahrzeugantriebe –Use case driven CO2 footprint of electrified powertrains . . . . . . . . . . . . . . .17 O. Ludwig, J. Muth, M. Gernuks, H. Schröder, T. Löscheter Horst, Volkswagen AG, Wolfsburg Prädiktion der Lebensdauer von Traktionsbatteriesystemen für reale Nutzungsszenarien . . . .33 M. Ufert, Professur für Fahrzeugmechatronik, Technische Universität Dresden; A. Batzdorf, L. Morawietz, IAM GmbH, Dresden Predictive Energy Management Strategies for Hybrid Electric Vehicles: eHorizon for Battery Management System. . . . . 49 M. ...

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